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Wordcloud of a year of headlines on the BBC News website

What does a year of the top items on the BBC News website look like?

I’ve been scraping the top ten headlines on the BBC News website, on the hour every hour, since July 2020.

In answering this question we’ll examine a year of these headlines from 28th July 2020 (the first full day of data scraping) to 27th July 2021.

In that period our data captures 10 headlines, every hour, every day, for a year. That means there are 10x24x365=87,600 headline ‘slots’ in this period.

A headline, of course, can run for a few hours. But we’ll count each ‘slot’ it occupies, because running for longer is likely to signify more importance.

Above, you can see a wordcloud representing the frequency of words in a year of those headlines.

The Top 50 most used words are as follows:

  Word Mentions
1 covid 12050
2 uk 7615
3 us 4524
4 new 4275
5 coronavirus 3888
6 england 3847
7 vaccine 3739
8 lockdown 3728
9 pm 3401
10 police 3120
11 trump 3052
12 update 2519
13 dies 2483
14 man 2417
15 rules 2372
16 first 2296
17 biden 2187
18 virus 1738
19 eu 1711
20 cases 1664
21 home 1664
22 covid19 1554
23 death 1547
24 nhs 1418
25 wales 1398
26 people 1396
27 deal 1373
28 school 1367
29 brexit 1357
30 jab 1334
31 back 1301
32 christmas 1274
33 rise 1243
34 found 1236
35 set 1231
36 travel 1217
37 two 1204
38 deaths 1178
39 ban 1142
40 test 1137
41 win 1113
42 may 1102
43 evening 1097
44 face 1088
45 children 1083
46 johnson 1074
47 attack 1071
48 trade 1070
49 dead 1069
50 plan 1068

It’s no surprise that pandemic-specific words dominated in this period:

  Word Mentions
1 covid 12050
5 coronavirus 3888
7 vaccine 3739
8 lockdown 3728
18 virus 1738
20 cases 1664
22 covid19 1554
24 nhs 1418
30 jab 1334
40 test 1137

The US election, presidential inauguration, and a lot of unrest and controversy around those happened in this period, explaining the ranking of these words:

  Word Mentions
3 us 4524
11 trump 3052
17 biden 2187

Brexit also happened in this period:

  Word Mentions
19 eu 1711
29 brexit 1357
48 trade 1070

You can view and reproduce the analysis behind this research in a Jupyter Notebook.